Vegetation and outdoor recess time at elementary schools: What are the connections?

Empirical and anecdotal evidence suggests that landscapes with more vegetation have a positive impact on children's focus, attention, and cognitive development. In school, children are able to regain focus, suppress impulses, and pay attention in class longer after exposure to natural settings. Because children spend much of their time in school, the amount and types of vegetation on school grounds may influence their development. Public elementary schools in the Commonwealth of Virginia (N = 988) were surveyed to examine correlations between school ground vegetation and outside recess. The number of trees on school grounds, the size of the school grounds, and the presence of sports fields were modestly correlated with greater outside recess time. These correlations support common sense because sports fields facilitate supervised play and larger school grounds provide space for sports fields and playgrounds and additional opportunities for free play. More trees on school grounds provide a welcoming environment for students and teachers, and encourage outside play. These results may help school personnel design and maintain school grounds that increase outdoor recess time.     

Comparison of Two Types of Metapopulation Models in Real and Artificial Landscapes

Abstract: Application of metapopulation models is becoming increasingly widespread in the conservation of species in fragmented landscapes. We provide one of the first detailed comparisons of two of the most common modeling techniques, incidence function models and stage-based matrix models, and test their accuracy in predicting patch occupancy for a real metapopulation. We measured patch occupancies and demographic rates for regional populations of the Florida scrub lizard (   Sceloporus woodi ) and compared the observed occupancies with those predicted by each model. Both modeling strategies predicted patch occupancies with good accuracy ( 77–80%) and gave similar results when we compared hypothetical management scenarios involving removal of key habitat patches and degradation of habitat quality. To compare the two modeling approaches over a broader set of conditions, we simulated metapopulation dynamics for 150 artificial landscapes composed of equal-sized patches (2–1024 ha) spaced at equal distances (50–750 m). Differences in predicted patch occupancy were small to moderate (<20%) for about 74% of all simulations, but 22% of the landscapes had differences openface> 50%. Incidence function models and stage-based matrix models differ in their approaches, assumptions, and requirements for empirical data, and our findings provide evidence that the two models can produce different results. We encourage researchers to use both techniques and further examine potential differences in model output. The feasibility of obtaining data for population modeling varies widely among species and limits the modeling approaches appropriate for each species. Understanding different modeling approaches will become increasingly important as conservation programs undertake the challenge of managing for multiple species in a landscape context.     

Regional status assessment of stony corals in the US Virgin Islands

States may protect coral reefs using biological water quality standards outlined by the Clean Water Act. This requires biological assessments with indicators sensitive to human disturbance and regional, probability-based survey designs. Stony coral condition was characterized on a regional scale for the first time in the nearshore waters of the US Virgin Islands (USVI). Coral composition, abundance, size, and health were assessed at 66 stations in the St. Croix region in fall 2007 and at 63 stations in the St. Thomas and St. John region in winter 2009. Indicators were chosen for their sensitivity to human disturbance. Both surveys were probability-based (random) designs with station locations preselected from areas covered by hardbottom and coral reef substrate. Taxa richness was as high as 21 species but more than half the area of both regions exhibited taxa richness of <10 species in the 25 m² transect area. Coral density was as high as 5 colonies m^?2 but more than half the area of both regions had <2 colonies m^?2. Both regions showed similar dominant species based on frequency of occurrence and relative abundance. Because of large colony sizes, Montastrea annularis provided more total surface area and live surface area than more abundant species. The surveys establish baseline regional conditions and provide a foundation for long-term regional monitoring envisioned by the USVI Department of Planning and Natural Resources. The probabilistic sampling design assures the data can be used in Clean Water Act reporting.     

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.     

Utility of North Atlantic Right Whale Museum Specimens for Assessing Changes in Genetic Diversity

Abstract: We examined six historical specimens of the endangered North Atlantic right whale ( Eubalaena glacialis ) using DNA isolated from documented baleen plates from the late nineteenth and early twentieth centuries. Sequences from the mitochondrial DNA (mtDNA) control region from these samples were compared with those from a near-exhaustive survey (269 of approximately 320 individuals) of the remaining right whales in the western North Atlantic Ocean. Our results suggest that there has been only relatively modest change in maternal lineage diversity over the past century in the North Atlantic right whale population. Any significant reduction in genetic variation in the species most likely occurred prior to the late nineteenth century. One historical specimen was from the last documented female capable of propagating one of the maternal lineages in the population today; no females in the existing population have been found to carry this mtDNA haplotype. Analysis of the only specimens from the eastern North Atlantic right whale population ever to be examined revealed that eastern and western North Atlantic right whales may not have been genetically differentiated populations. Loss of gene diversity experienced by North Atlantic right whales over the last century has been modest, and the six decades of protection have been successful in maintaining much of the maternal lineage diversity that was present in the late nineteenth century.     

Seasonal and spatial changes in the larval fish fauna within a large temperate Australian estuary

A total of 66814 fish larvae, representing 37 families and 74 species, were collected in samples taken monthly between January 1986 and April 1987 from 13 sites located at frequent intervals throughout the large Swan Estuary in south-western Australia. The Gobiidae was the most abundant family, comprising 88.2% of the total number of larvae, followed by the Clupeidae (3.4%), Engraulididae (2.9%) and Blenniidae (1.0%). The most abundant species were Pseudogobius olorum (53.3%), Arenigobius bifrenatus (31.2%) and Engraulis australis (2.9%). Abundance of fish larvae in the lower, middle and upper regions of the estuary each reached a maximum between mid-spring and early summer, 2 to 4 mo before the attainment of maximum temperatures. Larvae of species such as Nematalosa vlaminghi and Apogon rueppellii were collected only between November and February, whereas those of others such as P. olorum, E. australis and Leptatherina wallacei were present over many months. The times and locations of capture of larvae have been related to the distribution and breeding periods of the adults of these species. The mean monthly number of species was far greater in the lower than upper estuary (14.7 vs 2.7), whereas the reverse was true for mean monthly concentration (42 vs 197 larvae per 100 m³). Classification, using the abundance of each of the 74 species recorded at the different sites, showed that the composition of the larval fish fauna in the lower, middle and upper estuary differed markedly from each other. Most larvae caught in the lower estuary belonged to marine species, whereas those in the upper estuary almost exclusively represented species that spawn within the estuary. The fact that the larvae of the 59 species of marine teleosts recorded during this study were restricted mainly to the lower estuary, and yet contributed only 6.2% to the total numbers for the whole estuary, helps to account for the relatively high species diversity in this region. The lack of penetration of many of these larvae beyond the first 12.5 km of the estuary presumably reflects the weak tidal effect in the wide basins of the middle estuary and saline regions of the tributary rivers. The larvae of the 13 teleosts that typically spawn within the estuary contributed 93.8% to the total numbers of larvae. Most of these estuarine-spawned larvae belong to teleosts that deposit demersal eggs and/or exhibit parental care (egg-guarding and oral and pouch-brooding), characteristics which would maximize their chances of retention within the estuary.     

Bayesian areal wombling via adjacency modeling

Recently, public health professionals and other geostatistical researchers have shown increasing interest in boundary analysis, the detection or testing of zones or boundaries that reveal sharp changes in the values of spatially oriented variables. For areal data (i.e., data which consist only of sums or averages over geopolitical regions), Lu and Carlin (Geogr Anal 37: 265–285, 2005) suggested a fully model-based framework for areal wombling using Bayesian hierarchical models with posterior summaries computed using Markov chain Monte Carlo (MCMC) methods, and showed the approach to have advantages over existing non-stochastic alternatives. In this paper, we develop Bayesian areal boundary analysis methods that estimate the spatial neighborhood structure using the value of the process in each region and other variables that indicate how similar two regions are. Boundaries may then be determined by the posterior distribution of either this estimated neighborhood structure or the regional mean response differences themselves. Our methods do require several assumptions (including an appropriate prior distribution, a normal spatial random effect distribution, and a Bernoulli distribution for a set of spatial weights), but also deliver more in terms of full posterior inference for the boundary segments (e.g., direct probability statements regarding the probability that a particular border segment is part of the boundary). We illustrate three different remedies for the computing difficulties encountered in implementing our method. We use simulation to compare among existing purely algorithmic approaches, the Lu and Carlin (2005) method, and our new adjacency modeling methods. We also illustrate more practical modeling issues (e.g., covariate selection) in the context of a breast cancer late detection data set collected at the county level in the state of Minnesota.